{"total":118,"rows":[{"id":"2301.10921","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","created":"2023-01-26","cited_by_count":133,"area":null},{"id":"2208.07204","title":"USB: A Unified Semi-supervised Learning Benchmark for Classification","created":"2022-08-12","cited_by_count":95,"area":null},{"id":"2410.10777","title":"UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation","created":"2024-10-14","cited_by_count":54,"area":null},{"id":"2303.12993","title":"Backdoor Defense via Adaptively Splitting Poisoned Dataset","created":"2023-03-23","cited_by_count":43,"area":null},{"id":"2212.00334","title":"Parametric Information Maximization for Generalized Category Discovery","created":"2022-12-01","cited_by_count":39,"area":null},{"id":"2302.10586","title":"Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels","created":"2023-02-21","cited_by_count":37,"area":"diffusion"},{"id":"2403.14198","title":"Unleashing Unlabeled Data: A Paradigm for Cross-View Geo-Localization","created":"2024-03-21","cited_by_count":31,"area":null},{"id":"2405.00378","title":"Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation","created":"2024-05-01","cited_by_count":30,"area":null},{"id":"2210.03591","title":"Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery","created":"2022-10-07","cited_by_count":26,"area":null},{"id":"2303.11066","title":"Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data","created":"2023-03-20","cited_by_count":26,"area":null},{"id":"2304.06928","title":"CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery","created":"2023-04-14","cited_by_count":26,"area":null},{"id":"2308.13168","title":"IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization","created":"2023-08-25","cited_by_count":23,"area":null},{"id":"2306.07483","title":"Semi-supervised learning made simple with self-supervised clustering","created":"2023-06-13","cited_by_count":20,"area":null},{"id":"2308.06777","title":"Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning","created":"2023-08-13","cited_by_count":17,"area":null},{"id":"2301.03726","title":"Neighborhood-Regularized Self-Training for Learning with Few Labels","created":"2023-01-10","cited_by_count":14,"area":null},{"id":"2310.03013","title":"SemiReward: A General Reward Model for Semi-supervised Learning","created":"2023-10-04","cited_by_count":14,"area":"alignment"},{"id":"2303.13556","title":"ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-supervised Learning","created":"2023-03-22","cited_by_count":13,"area":null},{"id":"2211.11086","title":"An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning","created":"2022-11-20","cited_by_count":12,"area":null},{"id":"2308.06692","title":"SimMatchV2: Semi-Supervised Learning with Graph Consistency","created":"2023-08-13","cited_by_count":12,"area":null},{"id":"2308.08872","title":"Towards Semi-supervised Learning with Non-random Missing Labels","created":"2023-08-17","cited_by_count":12,"area":null},{"id":"2503.06277","title":"STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification","created":"2025-03-08","cited_by_count":12,"area":null},{"id":"2308.07509","title":"Boosting Semi-Supervised Learning by bridging high and low-confidence predictions","created":"2023-08-15","cited_by_count":11,"area":null},{"id":"2503.18244","title":"CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation","created":"2025-03-23","cited_by_count":11,"area":"distill"},{"id":"2312.07006","title":"Mixed Pseudo Labels for Semi-Supervised Object Detection","created":"2023-12-12","cited_by_count":10,"area":null},{"id":"2305.12715","title":"Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations","created":"2023-05-22","cited_by_count":9,"area":null},{"id":"2311.10572","title":"SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning","created":"2023-11-17","cited_by_count":9,"area":null},{"id":"2403.12986","title":"BaCon: Boosting Imbalanced Semi-supervised Learning via Balanced Feature-Level Contrastive Learning","created":"2024-03-04","cited_by_count":9,"area":null},{"id":"2409.19659","title":"Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery","created":"2024-09-29","cited_by_count":9,"area":"distill"},{"id":"2305.10397","title":"RelationMatch: Matching In-batch Relationships for Semi-supervised Learning","created":"2023-05-17","cited_by_count":8,"area":null},{"id":"2307.08919","title":"Systematic comparison of semi-supervised and self-supervised learning for medical image classification","created":"2023-07-18","cited_by_count":8,"area":null},{"id":"2310.15787","title":"SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning","created":"2023-10-24","cited_by_count":8,"area":null},{"id":"2312.01619","title":"How Many Validation Labels Do You Need? Exploring the Design Space of Label-Efficient Model Ranking","created":"2023-12-04","cited_by_count":8,"area":null},{"id":"2208.05853","title":"MultiMatch: Multi-task Learning for Semi-supervised Domain Generalization","created":"2022-08-11","cited_by_count":7,"area":null},{"id":"2312.12237","title":"Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-Grained Learning","created":"2023-12-19","cited_by_count":7,"area":null},{"id":"2507.01884","title":"Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification","created":"2025-07-02","cited_by_count":7,"area":null},{"id":"2301.05158","title":"SemPPL: Predicting pseudo-labels for better contrastive representations","created":"2023-01-12","cited_by_count":6,"area":null},{"id":"2301.10127","title":"Improving Open-Set Semi-Supervised Learning with Self-Supervision","created":"2023-01-24","cited_by_count":6,"area":null},{"id":"2310.17455","title":"OTMatch: Improving Semi-Supervised Learning with Optimal Transport","created":"2023-10-26","cited_by_count":6,"area":null},{"id":"2404.11003","title":"InfoMatch: Entropy Neural Estimation for Semi-Supervised Image Classification","created":"2024-04-17","cited_by_count":6,"area":null},{"id":"2409.05122","title":"PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation","created":"2024-09-08","cited_by_count":6,"area":null},{"id":"2506.02334","title":"Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization","created":"2025-06-03","cited_by_count":6,"area":null},{"id":"2212.06643","title":"Boosting Semi-Supervised Learning with Contrastive Complementary Labeling","created":"2022-12-13","cited_by_count":5,"area":null},{"id":"2309.03598","title":"Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning","created":"2023-09-07","cited_by_count":5,"area":null},{"id":"2310.05141","title":"Transferable Availability Poisoning Attacks","created":"2023-10-08","cited_by_count":5,"area":"safety"},{"id":"2412.10741","title":"RegMixMatch: Optimizing Mixup Utilization in Semi-Supervised Learning","created":"2024-12-14","cited_by_count":5,"area":null},{"id":"2305.12074","title":"DisCo: Distilled Student Models Co-training for Semi-supervised Text Mining","created":"2023-05-20","cited_by_count":4,"area":"distill"},{"id":"2307.04610","title":"SPLAL: Similarity-based pseudo-labeling with alignment loss for semi-supervised medical image classification","created":"2023-07-10","cited_by_count":4,"area":null},{"id":"2312.03325","title":"FAGC:Feature Augmentation on Geodesic Curve in the Pre-Shape Space","created":"2023-12-06","cited_by_count":4,"area":null},{"id":"2303.02998","title":"Pseudo-label Correction and Learning For Semi-Supervised Object Detection","created":"2023-03-06","cited_by_count":3,"area":null},{"id":"2303.12091","title":"Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning","created":"2023-03-21","cited_by_count":3,"area":null},{"id":"2405.14506","title":"SIAVC: Semi-Supervised Framework for Industrial Accident Video Classification","created":"2024-05-23","cited_by_count":3,"area":null},{"id":"2406.15763","title":"AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning","created":"2024-06-22","cited_by_count":3,"area":null},{"id":"2407.11735","title":"ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection","created":"2024-07-16","cited_by_count":3,"area":null},{"id":"2409.01448","title":"FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition","created":"2024-09-02","cited_by_count":3,"area":null},{"id":"2409.17512","title":"SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning","created":"2024-09-26","cited_by_count":3,"area":null},{"id":"2503.00884","title":"Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model","created":"2025-03-02","cited_by_count":3,"area":null},{"id":"2508.05316","title":"Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning","created":"2025-08-07","cited_by_count":3,"area":null},{"id":"2209.14205","title":"Prompt-driven efficient Open-set Semi-supervised Learning","created":"2022-09-28","cited_by_count":2,"area":null},{"id":"2305.14813","title":"Semi-Supervised and Long-Tailed Object Detection with CascadeMatch","created":"2023-05-24","cited_by_count":2,"area":null},{"id":"2306.01222","title":"Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2309.03469","title":"Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size","created":"2023-09-07","cited_by_count":2,"area":null},{"id":"2310.15764","title":"Debiasing, calibrating, and improving Semi-supervised Learning performance via simple Ensemble Projector","created":"2023-10-24","cited_by_count":2,"area":null},{"id":"2403.15567","title":"Do not trust what you trust: Miscalibration in Semi-supervised Learning","created":"2024-03-22","cited_by_count":2,"area":null},{"id":"2403.16469","title":"Learning from Reduced Labels for Long-Tailed Data","created":"2024-03-25","cited_by_count":2,"area":null},{"id":"2403.18144","title":"Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning","created":"2024-03-26","cited_by_count":2,"area":null},{"id":"2409.07292","title":"A Unified Contrastive Loss for Self-Training","created":"2024-09-11","cited_by_count":2,"area":null},{"id":"2409.13977","title":"Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled Data","created":"2024-09-21","cited_by_count":2,"area":null},{"id":"2411.10364","title":"Forming Auxiliary High-confident Instance-level Loss to Promote Learning from Label Proportions","created":"2024-11-15","cited_by_count":2,"area":null},{"id":"2211.09593","title":"NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning","created":"2022-11-17","cited_by_count":1,"area":null},{"id":"2212.04211","title":"Evaluating Zero-cost Active Learning for Object Detection","created":"2022-12-08","cited_by_count":1,"area":null},{"id":"2301.13569","title":"NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning","created":"2023-01-31","cited_by_count":1,"area":null},{"id":"2304.04441","title":"Self-training with dual uncertainty for semi-supervised medical image segmentation","created":"2023-04-10","cited_by_count":1,"area":null},{"id":"2308.10761","title":"CoNe: Contrast Your Neighbours for Supervised Image Classification","created":"2023-08-21","cited_by_count":1,"area":null},{"id":"2308.14058","title":"Pruning the Unlabeled Data to Improve Semi-Supervised Learning","created":"2023-08-27","cited_by_count":1,"area":null},{"id":"2311.06054","title":"Refining the ONCE Benchmark with Hyperparameter Tuning","created":"2023-11-10","cited_by_count":1,"area":null},{"id":"2404.17978","title":"A Method of Moments Embedding Constraint and its Application to Semi-Supervised Learning","created":"2024-04-27","cited_by_count":1,"area":null},{"id":"2405.06227","title":"MaskMatch: Boosting Semi-Supervised Learning Through Mask Autoencoder-Driven Feature Learning","created":"2024-05-10","cited_by_count":1,"area":null},{"id":"2407.15873","title":"CRMSP: A Semi-supervised Approach for Key Information Extraction with Class-Rebalancing and Merged Semantic Pseudo-Labeling","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2412.00883","title":"Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence","created":"2024-12-01","cited_by_count":1,"area":null},{"id":"2502.12584","title":"Enhancing Semi-supervised Learning with Zero-shot Pseudolabels","created":"2025-02-18","cited_by_count":1,"area":null},{"id":"2503.00286","title":"A Unified Framework for Heterogeneous Semi-supervised Learning","created":"2025-03-01","cited_by_count":1,"area":null},{"id":"2503.10693","title":"Knowledge Consultation for Semi-Supervised Semantic Segmentation","created":"2025-03-12","cited_by_count":1,"area":null},{"id":"2506.07801","title":"MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification","created":"2025-06-09","cited_by_count":1,"area":null},{"id":"2509.16516","title":"LLM-Guided Co-Training for Text Classification","created":"2025-09-20","cited_by_count":1,"area":null},{"id":"2211.09929","title":"Contrastive Credibility Propagation for Reliable Semi-Supervised Learning","created":"2022-11-17","cited_by_count":0,"area":null},{"id":"2310.05082","title":"Cross-head mutual Mean-Teaching for semi-supervised medical image segmentation","created":"2023-10-08","cited_by_count":0,"area":null},{"id":"2310.14718","title":"Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Images","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2311.01646","title":"SemiGPC: Distribution-Aware Label Refinement for Imbalanced Semi-Supervised Learning Using Gaussian Processes","created":"2023-11-03","cited_by_count":0,"area":null},{"id":"2311.04055","title":"Feature Space Renormalization for Semi-supervised Learning","created":"2023-11-07","cited_by_count":0,"area":null},{"id":"2311.15728","title":"Adinkra Symbol Recognition using Classical Machine Learning and Deep Learning","created":"2023-11-27","cited_by_count":0,"area":null},{"id":"2312.06169","title":"Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions","created":"2023-12-11","cited_by_count":0,"area":null},{"id":"2404.05976","title":"A Cyber Manufacturing IoT System for Adaptive Machine Learning Model Deployment by Interactive Causality Enabled Self-Labeling","created":"2024-04-09","cited_by_count":0,"area":null},{"id":"2404.11947","title":"VCC-INFUSE: Towards Accurate and Efficient Selection of Unlabeled Examples in Semi-supervised Learning","created":"2024-04-18","cited_by_count":0,"area":null},{"id":"2405.14516","title":"Towards Realistic Long-tailed Semi-supervised Learning in an Open World","created":"2024-05-23","cited_by_count":0,"area":null},{"id":"2405.16093","title":"Diverse Teacher-Students for Deep Safe Semi-Supervised Learning under Class Mismatch","created":"2024-05-25","cited_by_count":0,"area":"distill"},{"id":"2405.16930","title":"From Obstacles to Resources: Semi-supervised Learning Faces Synthetic Data Contamination","created":"2024-05-27","cited_by_count":0,"area":null},{"id":"2406.01086","title":"Diverse Subset Selection via Norm-Based Sampling and Orthogonality","created":"2024-06-03","cited_by_count":0,"area":null},{"id":"2409.18316","title":"Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective","created":"2024-09-26","cited_by_count":0,"area":null},{"id":"2411.13001","title":"Collaborative Feature-Logits Contrastive Learning for Open-Set Semi-Supervised Object Detection","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2412.17547","title":"Probability-density-aware Semi-supervised Learning","created":"2024-12-23","cited_by_count":0,"area":null}],"next_cursor":"100"}